README.md

---
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
 results: []
---

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# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4400
- Accuracy: 0.91

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6505 | 1.0 | 113 | 0.6775 | 0.77 |
| 0.2847 | 2.0 | 226 | 0.6989 | 0.78 |
| 0.4559 | 3.0 | 339 | 0.5821 | 0.85 |
| 0.1643 | 4.0 | 452 | 0.6462 | 0.85 |
| 0.0083 | 5.0 | 565 | 0.6071 | 0.87 |
| 0.0281 | 6.0 | 678 | 0.5648 | 0.87 |
| 0.0001 | 7.0 | 791 | 0.4394 | 0.92 |
| 0.0002 | 8.0 | 904 | 0.4378 | 0.9 |
| 0.1345 | 9.0 | 1017 | 0.4299 | 0.9 |
| 0.0002 | 10.0 | 1130 | 0.4400 | 0.91 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3